Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add nota-america/forgecat-agent-profiles --skill performance-reviewgit clone --depth 1 https://github.com/nota-america/forgecat-agent-profilesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nota-america/forgecat-agent-profiles/performance-review)<a href="https://agentmods.dev/skills/nota-america/forgecat-agent-profiles/performance-review"><img src="https://agentmods.dev/badge/skills/nota-america/forgecat-agent-profiles/performance-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nota-america/forgecat-agent-profiles/performance-review"><img src="https://agentmods.dev/badge/skills/nota-america/forgecat-agent-profiles/performance-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00061 | $0.01141 |
| Opus 5 | $0.00030 | $0.00571 |
| Sonnet 5 | $0.00012 | $0.00228 |
| Haiku 4.5 | $0.00006 | $0.00114 |
Grade A, and why
performance-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
89% identical to performance-review — 10 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/performance-review
If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md (
.forgecat/profiles/@forgecat/anthropics_knowledge-work-plugins_human-resources/CONNECTORS.md).
Generate performance review templates and help structure feedback.
Usage
/performance-review $ARGUMENTS
Modes
/performance-review self-assessment # Generate self-assessment template
/performance-review manager [employee] # Manager review template for a specific person
/performance-review calibration # Calibration prep document
If no mode is specified, ask what type of review they need.
Output — Self-Assessment Template
## Self-Assessment: [Review Period]
### Key Accomplishments
[List your top 3-5 accomplishments this period. For each, describe the situation, your contribution, and the impact.]
1. **[Accomplishment]**
- Situation: [Context]
- Contribution: [What you did]
- Impact: [Measurable result]
### Goals Review
| Goal | Status | Evidence |
|------|--------|----------|
| [Goal from last period] | Met / Exceeded / Missed | [How you know] |
### Growth Areas
[Where did you grow? New skills, expanded scope, leadership moments.]
### Challenges
[What was hard? What would you do differently?]
### Goals for Next Period
1. [Goal — specific and measurable]
2. [Goal]
3. [Goal]
### Feedback for Manager
[How can your manager better support you?]
Output — Manager Review
## Performance Review: [Employee Name]
**Period:** [Date range] | **Manager:** [Your name]
### Overall Rating: [Exceeds / Meets / Below Expectations]
### Performance Summary
[2-3 sentence overall assessment]
### Key Strengths
- [Strength with specific example]
- [Strength with specific example]
### Areas for Development
- [Area with specific, actionable guidance]
- [Area with specific, actionable guidance]
### Goal Achievement
| Goal | Rating | Comments |
|------|--------|----------|
| [Goal] | [Rating] | [Specific observations] |
### Impact and Contributions
[Describe their biggest contributions and impact on the team/org]
### Development Plan
| Skill | Current | Target | Actions |
|-------|---------|--------|---------|
| [Skill] | [Level] | [Level] | [How to get there] |
### Compensation Recommendation
[Promotion / Equity refresh / Adjustment / No change — with justification]
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 154 lines · 61 tokens per session scan A c93ab887c66f
performance-review is a skill published in the GitHub repository nota-america/forgecat-agent-profiles (66 stars, last pushed today), licensed Apache-2.0. It adds 61 tokens to every session and 1,141 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to performance-review, differing in 10 lines, and is treated as a copy.
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